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Design and Build A Customer-Finding Application For Leko Restaurant Using The K-Means Algorithm Mohamad Yusuf; Muhaimin Hasanudin; Ifan Prihandi
IJISTECH (International Journal of Information System and Technology) Vol 6, No 2 (2022): August
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Warung Makan Leko is one of the restaurants in the Jakarta area that offers local cuisine, a diverse menu and delivery orders via phone order. Customers are one source of income for Warung Makan Leko. The amount of competition makes Warung Makan Leko have difficulty in retaining loyal customers. For this reason, further analysis is needed to find out who these potential customers are. Then an application was developed to classify customer data using the K-Means (clustering) algorithm. The data used as an example in this study is the sales transaction data of Warung Makan Leko. Run the process to calculate the total sales to customers and the number of transactions with customers to classify customer data. The K-Means clustering method tries to group the existing data into groups. Data in groups have the same properties. Customer data is grouped into two clusters, no and implicit. Each cluster is then classified based on the prioritized criteria. The cluster with the highest centroid value is the cluster that is rewarded, and the cluster with the lowest centroid value is the non-rewarded cluster. The results of this process form clusters, which are used for advice and consideration to determine sales strategy, namely to reward customers who rank higher in the cluster

Design and Build A Customer-Finding Application For Leko Restaurant Using The K-Means Algorithm Mohamad Yusuf; Muhaimin Hasanudin; Ifan Prihandi
IJISTECH (International Journal of Information System and Technology) Vol 6, No 2 (2022): August
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v6i2.238

Warung Makan Leko is one of the restaurants in the Jakarta area that offers local cuisine, a diverse menu and delivery orders via phone order. Customers are one source of income for Warung Makan Leko. The amount of competition makes Warung Makan Leko have difficulty in retaining loyal customers. For this reason, further analysis is needed to find out who these potential customers are. Then an application was developed to classify customer data using the K-Means (clustering) algorithm. The data used as an example in this study is the sales transaction data of Warung Makan Leko. Run the process to calculate the total sales to customers and the number of transactions with customers to classify customer data. The K-Means clustering method tries to group the existing data into groups. Data in groups have the same properties. Customer data is grouped into two clusters, no and implicit. Each cluster is then classified based on the prioritized criteria. The cluster with the highest centroid value is the cluster that is rewarded, and the cluster with the lowest centroid value is the non-rewarded cluster. The results of this process form clusters, which are used for advice and consideration to determine sales strategy, namely to reward customers who rank higher in the cluster

Improving Vehicle Detection in Challenging Datasets: YOLOv5s and Frozen Layers Analysis Ahmad Nanda Yuma Rafi; Mohamad Yusuf
International Journal of Informatics and Computation Vol. 5 No. 2 (2023): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v5i2.64

Small datasets and imbalanced classes often cause problems when it used as primary research material. In case of classification and object detection, some researchers proposed Transfer Learning (TF) with several frozen layers. Moreover, YOLO (You Only Look Once) is one of the algorithms that works in real-time object detection. In this research, we focused on evaluating the YOLOv5s version of detecting vehicles in small and imbalanced datasets. The original YOLOv5s were trained and compared with YOLOv5s with freezing layers method (10 and 24 frozen layers). The experimental results of original YOLOv5s were precision score of 0.779, recall value of 0.933, mAP@0.5 of 0.93 and mAP@0.5:0.95 of 0.684 while YOLOv5s with 10 frozen layers where precision score was decreased to 0.639, but the other value increase with recall value of 0.939, mAP@0.5 of 0.951 and mAP@0.5:0.95 of 0.732. Overall, the version with 10 frozen layers demonstrated superior performance in addressing the challenges of small and imbalanced datasets, particularly excelling in recall and mAP metrics.

Line Crossing Detector System for Real-Time Over-Taking Vehicle Detection Ahmad Nanda Yuma Rafi; Mohamad Yusuf
International Journal of Informatics and Computation Vol. 6 No. 1 (2024): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v6i1.72

This study introduces a novel method for detecting overtaking vehicles by integrating Virtual Line Detection with the YOLOv8n algorithm. The objective is to enhance road safety by accurately identifying and tracking vehicles as they overtake, which is crucial for preventing. The research demonstrates the effectiveness of this approach, achieving a detection accuracy rate of 80.95% using line crossing detection techniques. This high level of accuracy underscores the potential of the system to reliably identify overtaking maneuvers in traffic conditions. Furthermore, this innovative method holds promising implications for enhancing safety riding by providing realtime alerts to drivers and preventing infrastructure loss resulting from traffic incidents. Our findings suggest that integrating advanced detection algorithms like YOLOv8n with virtual line detection can be a viable solution for modern traffic safety challenges.

Pembelajaran Dasar Keamanan Pengguna Sosial Media Pada Tim PKK Petugas Kelurahan Duri Kepa Kebon Jeruk Jakarta Barat Roy Mubarak; Mohamad Yusuf
Jurnal Abdimas Indonesia Vol. 4 No. 2 (2024): April-Juni 2024
Publisher : Perkumpulan Dosen Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53769/jai.v4i2.704

Media sosial adalah platform digital yang memungkinkan pengguna untuk berinteraksi, berbagi konten, dan terhubung dengan orang lain secara online. Ini adalah sarana komunikasi yang sangat populer di seluruh dunia, memungkinkan individu, kelompok, dan organisasi untuk berbagi informasi, pandangan, dan pengalaman. Contoh dari platform media sosial adalah: Facebook, Instagram, Twitter LinkedIn, YouTube, Snapchat, TikTok, WhatsApp, Reddit dan Pinterest. Platform-platform ini menawarkan berbagai fitur dan pengalaman, dan masing-masing memiliki komunitas pengguna yang unik. Namun, penting untuk diingat bahwa penggunaan media sosial juga membawa risiko terkait privasi, keamanan, dan kesehatan mental, sehingga penting untuk menggunakan platform-platform tersebut dengan bijak. Contoh dari ancaman keamanan dari penggunaan sosial media adalah: Privasi dan Keamanan, Cyberbullying, Penyebaran Informasi Palsu (Hoaks), Pencurian identitas, Penipuan Online, Pemerasan Online dan lainnya. Sehingga keamanan dalam penggunaan media sosial adalah suatu hal yang sangat penting, mengingat risiko yang terkait dengan privasi, keamanan, dan kesehatan mental. Sehingga kegiatan pengabdian ini memang dirasakan banyak manfaatnya bagi masyarakat, salah satunya adalah upaya pencegahan dini dari upaya kejahatan dunia maya khususnya yang bersumber dari dampak penggunaan sosial media serta bagaimana cara bersosial media dengan bijak. Kebutuhan akan pemaparan dan pelatihan ini direalisasikan melalui kegiatan Pengabdian kepada Masyarakat (PkM) yang dilakukan oleh dosen dan mahasiswa sebagai salah satu Tridharma Perguruan Tinggi.

Penerapan Bahasa Pemrograman HTML Python sebagai perangkat pendukung dalam pelayanan Masyarakat Pada Tim PKK Kelurahan Duri Kepa Kebon Jeruk Jakarta Barat Mohamad Yusuf; Roy Mubarak; Rushendra Rushendra; Siti Maesaroh; Nungky Awang Candra
Jurnal Abdimas Indonesia Vol. 5 No. 1 (2025): Januari-Maret 2025
Publisher : Perkumpulan Dosen Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34697/jai.v5i1.1327

Tim Pemberdayaan dan Kesejahteraan Keluarga (PKK) di Kecamatan Duri Kepa berperan penting dalam menyebarkan informasi dan mendukung pengambilan keputusan tentang kesehatan masyarakat. Dengan meningkatnya kebutuhan akan solusi berbasis web, pengetahuan tentang teknologi seperti HTML, CSS, dan Python menjadi semakin krusial. Teknologi ini memungkinkan pengembangan sistem informasi yang lebih interaktif dan efektif, bahkan untuk pemula. Untuk menghadapi tantangan ini, program pelatihan telah disiapkan untuk memberikan anggota PKK keterampilan yang diperlukan dalam pengembangan web. Pelatihan ini menerapkan metode pembelajaran interaktif dan langsung di laboratorium universitas, dengan penekanan pada praktik HTML dan Python. Metode ini memberikan kesempatan bagi peserta untuk menerapkan keterampilan yang diperoleh dalam proyek berbasis web yang relevan dengan tugas mereka di PKK. Hasil dari kegiatan ini menunjukkan bahwa pelatihan berlangsung sukses dan peserta menunjukkan antusiasme yang tinggi. Mereka merasa nyaman dalam mengikuti pelatihan dan mampu menggunakan pengetahuan tentang HTML dan Python untuk membuat aplikasi sederhana. Program ini diharapkan dapat meningkatkan efektivitas intervensi kesehatan di tingkat komunitas serta mendukung pengambilan keputusan yang berbasis data dan berkelanjutan dalam konteks kesehatan masyarakat.

SOSIALISASI PENGENALAN APLIKASI STUNTING DAN TUMBUH KEMBANG BALITA PADA DESA CIPUTRI –KABUPATEN CIANJUR Hakim, Lukman; Santoso, Hadi; Yusuf, Mohamad
Jurnal Pengabdian dan Kewirausahaan Vol 9, No 1 (2025): Jurnal Pengabdian dan Kewirausahaan
Publisher : Universitas Bunda Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30813/jpk.v9i1.8190

Government Policies on Improving Nutritious Eating as a Priority in Combating Stunting The government’s policy to enhance nutritious eating is currently a priority in addressing stunting, as outlined in Presidential Regulation No. 72 of 2021 on Stunting Reduction. Stunting is a growth impairment condition caused by recurrent malnutrition. Ciputri Village, located in Pacet District, Cianjur Regency, with an area of 6.36 hectares and comprising four hamlets, still has a stunting prevalence of 1.03% among toddlers. A community service program involving LLDIKTI 3, in collaboration with the Cianjur Regency and several universities in Jakarta, was conducted. The purpose of the program was to provide understanding and socialization on the impacts and factors contributing to stunting in toddlers, as well as the use of a stunting application for monitoring the growth and development history of toddlers. The community service activities included preparatory observations and implementation on November 13-14, 2024. The program involved the presentation of the stunting and growth monitoring application and explanations of facial recognition for accessing the application. The program was attended by 25 participants, and the results were evaluated through a questionnaire. Based on the questionnaire, the expectation score was 3.52, while the reality score was 3.48 on a scale of 1-4, indicating overall satisfaction with the community service program.

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